Evidence map›Paper›PMID 41347166›Full record

ArticleFrontiers in pharmacology2025

Comparative effectiveness and pharmacological fingerprints of indobufen versus rivaroxaban in patients with chronic kidney disease: a single-center, real-world study.

Lijun Zhang, Mingbo Liu, Tingting Huang, He Zhang, Chuanfu Huang, Zhenbin Pan, Zhao Chen, Jun Ning, Jiameng Tang

Abstract read
In one paragraph

Article in Frontiers in pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Lijun ZhangDepartment of Nephrology, The First People's Hospital of Qinzhou, The Tenth Affiliated Hospital of Guangxi Medical University, Qinzhou, Guangxi, China.
Mingbo LiuDepartment of Laboratory Medicine, The First People's Hospital of Qinzhou, The Tenth Affiliated Hospital of Guangxi Medical University, Qinzhou, Guangxi, China.
Tingting HuangDepartment of Medical Statistics, The First People's Hospital of Qinzhou, The Tenth Affiliated Hospital of Guangxi Medical University, Qinzhou, Guangxi, China.
He ZhangDepartment of Nephrology, The First People's Hospital of Qinzhou, The Tenth Affiliated Hospital of Guangxi Medical University, Qinzhou, Guangxi, China.
Chuanfu HuangDepartment of Nephrology, The First People's Hospital of Qinzhou, The Tenth Affiliated Hospital of Guangxi Medical University, Qinzhou, Guangxi, China.
Zhenbin PanDepartment of Nephrology, The First People's Hospital of Qinzhou, The Tenth Affiliated Hospital of Guangxi Medical University, Qinzhou, Guangxi, China.
Zhao ChenDepartment of Nephrology, The First People's Hospital of Qinzhou, The Tenth Affiliated Hospital of Guangxi Medical University, Qinzhou, Guangxi, China.
Jun NingDepartment of Nephrology, The First People's Hospital of Qinzhou, The Tenth Affiliated Hospital of Guangxi Medical University, Qinzhou, Guangxi, China.
Jiameng TangDepartment of Laboratory Medicine, The First People's Hospital of Qinzhou, The Tenth Affiliated Hospital of Guangxi Medical University, Qinzhou, Guangxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Antithrombotic management in Chronic Kidney Disease (CKD) is a clinical dilemma. This study aimed to empirically evaluate the " Methods: In this retrospective cohort study (2020-2024), we analyzed CKD patients treated with indobufen or rivaroxaban. A multi-stage analysis first used machine learning to assess baseline cohort comparability, overcoming limitations of p-value-based tests. Subsequently, a Linear Mixed Model (LMM), adjusted for confounders including polypharmacy, assessed independent drug effects on in-hospital thrombosis, hemorrhage, and longitudinal laboratory markers. Results: Machine learning demonstrated the clinical comparability of the indobufen and rivaroxaban cohorts. The incidence of in-hospital thrombosis was numerically lower in the indobufen group (3.65% vs. 7.58%; Conclusion: In this real-world CKD cohort, indobufen and rivaroxaban demonstrated comparable clinical effectiveness and safety. Combining machine learning with longitudinal models helps to statistically adjust for complex confounders like polypharmacy, thereby providing a more robust estimate of a drug's independent effect.

Indexed as

chronic kidney disease (CKD)indobufenlarge language model (LLM)linear mixed model (LMM)real-world studyrivaroxaban

Identifiers

PMID41347166
PMCPMC12672237

What Socratic holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.